The paper aims to provide a framework for mitigating the detrimental effects of chasing performance; by putting historical performance in its “proper analytical perspective”, where the focus is on the investment process and historical performance plays a secondary role.

David Schofield, president of the international division for the firm, which adopts a unique investment process based on the mathematical foundation of Stochastic Portfolio Theory, believes a rudimentary screen on process should be preferred over the common default screening on numbers only.

“Investors have to have some sort of screen to narrow the field but by basing it on performance you are probably excluding some good with the bad. The key thing is to attempt to identify the process that makes a priori sense, but most are based on financial theory and equity assumptions,” he says.

“Most sophisticated investors pay more attention to investment process, over performance, but it is still often a secondary attention – the short list still arises through a performance filter. And even those institutional investors hiring on process will fire on performance.”

In the INTECH paper, “Chasing performance is a dangerous game,” authors, Robert Ferguson, Jason Greene and Carl Moss, use a mathematically-based parable to demonstrate the shortfalls of using performance to measure managers.

In the working example (see the paper here) it shows the probability that the good manager beats 20 bad managers over a 10-year period is only about 9.6 per cent.

“This implies that chasing performance leaves the investor with the good manager only about 9.6 per cent of the time and with a bad manager about 90.4 per cent of the time. The investor’s average relative return will be only 19.3 bps annually, his tracking error will be 980.7 bps and his information ratio will only be 0.024. This compared with 200 bps, 800 bps, and 0.25 for the good manager.

“Sceptics might argue that the number of managers at a finals presentation typically is far less than 20. This misses the point. The adverse filtering on historical performance begins early in the manager selection process. The universe of investment managers that the finalists are drawn from far exceeds 20. The problem may actually be worse than depicted here.”

The paper also explores the argument that a good manager may beat bad managers over time and all that is required is a longer historical performance record.

“For manager skill to have a proper opportunity to assert itself there has to have a reasonable length of time and three to five years is nowhere near long enough,” Schofield says.

In fact, the paper, shows that based on numbers alone it would take 157 years to have 75 per cent confidence that the good manager, in the paper’s example, will beat all the bad managers.

Given the fact it is common practice to filter managers using performance, Schofield believes at the least the limitations of doing that need to be more transparent, and further, that academic studies to assess managers according to process are needed.

“Given the fact an initial focus on numbers is almost unavoidable, people doing that analysis need to be aware of limitations of that analysis, and the role of luck,” he says.

Ironically, for the firm whose corridors are filled with mathematicians, INTECH’s view is a focus on more qualitative rather than pure quantitative analysis for manager selection would be beneficial.

“There is no real certainty in choosing a manager, but the starting point should be the process and then the context of that should be the performance. Investors should look at what needs to happen to deliver the alpha. If not, you may as well throw darts at a dart board. If a manager has had an unusually good or unusually bad run you need to look under the bonnet. Are they still doing the same thing, is the company the same, is the market the same.”

Schofield says this is true of listed products, but perhaps more so for unlisted asset classes where the numbers are less transparent, and it is difficult to measure performance.